DC-WUnet: An Underwater Ranging Signal Enhancement Network Optimized with Depthwise Separable Convolution and Conformer

Marine ship-radiated noise and multipath Doppler effect reduce the positioning accuracy of linear frequency modulation (LFM) signals in ocean waveguide environments. However, the assumption of Gaussian noise underlying most time–frequency domain algorithms limits their effectiveness in mitigating non-Gaussian interference. To address this issue, we propose a Deep-separable Conformer Wave-Unet (DC-WUnet)-based underwater acoustic signal enhancement network designed to reconstruct signals from interference and noise. The encoder incorporates the Conformer module and skip connections to enhance the network’s multiscale feature extraction capability. Meanwhile, the network introduces depthwise separable convolution to reduce the number of parameters and improve computational efficiency. The decoder applies a slope-based linear interpolation method for upsampling to avoid introducing high-frequency noise during decoding. Additionally, the loss function employs joint time–frequency domain constraints to prevent signal loss and compression, particularly under low Signal-to-Noise Ratio (SNR) conditions. Experimental evaluations under an SNR of −10 dB indicate that the proposed method achieves at least a 32% improvement in delay estimation accuracy and a 2.3 dB enhancement in output SNR relative to state-of-the-art baseline algorithms. Consistent performance advantages are also observed under varying SNR conditions, thereby validating the effectiveness of the proposed approach in shipborne noisy environments.